Spark Structured Streaming - Using Kudu as Source

Question

I want to use PySpark in order to stream a Kudu table, process the streaming data and stream it back into another Kudu table.

Below is the driver code I've been trying out

from pyspark.sql import SparkSession

spark = SparkSession \
    .builder \
    .appName("Kudu-stream") \
    .getOrCreate()

df = spark \
    .readStream \
    .format("org.apache.kudu.spark.kudu") \
    .option("kudu.master","example:7051") \
    .option("kudu.table","db.source_test") \
    .load()

def saveToKudu(batchDF, batchID):
  batchDF.write \
  .format("org.apache.kudu.spark.kudu") \
  .option("kudu.master","example:7051") \
  .option("kudu.table","db.sink_test") \
  .mode("append") \
  .save()

query = df \
  .writeStream \
  .outputMode("append") \
  .foreachBatch(saveToKudu) \
  .option("checkpointLocation","hdfs://example:8020/path/to/checkpoint/") \
  .start()

query.awaitTermination()

This is the error message I've been getting.

py4j.protocol.Py4JJavaError: An error occurred while calling o40.load.
: java.lang.UnsupportedOperationException: Data source org.apache.kudu.spark.kudu does not support streamed reading

Is there a way to readStream directly from a Kudu table?

Extra: is it possible to writeStream to Kudu without using foreach or foreachBatch?